The objective of the proposed research is to develop analytical techniques as well as conduct the analysis of precipitation microphysical parameters (such as Drop Size Distribution parameters) on a global scale, to derive microphysical inferences of precipitation variations at global and regional scales. In order to make an impact on any global scale observations, the precipitation parameters to be observed need to be developed based on observations such as TRMM. The specific topics to be addressed are a) Development of self organizing and classification algorithms that will classify the PR data profiles on a global scale to regions of microphysical significance b) development of global maps of raindrop size distribution parameters such as the median drop diameter and the normalized concentration c) development and analysis of PR based classification of precipitation using vertical profiles d) develop a neural network based strategy to transfer precipitation estimates from ground radars to TRMM PR e) Collect and analyze the coordinated data sets between TRMM PR and ground polarimetric radars that are part of the ground validation program and other target of opportunity observations to ensure transfer of quantitative and qualitative microphysical interpretations to TRMM observations. In addition the PI proposes to play a significant role in the design and deployment of Ground radar and other in-situ sampling infrastructure for the GPM Ground Validation program, including the matching of the space borne and ground polarimetric observation of precipitation as well as hydrometeor classification.
